Parametric estimation for linear stochastic differential equations driven by mixed fractional Brownian motion

DOI10.1080/07362994.2018.1462714zbMath1411.62067OpenAlexW2801688642MaRDI QIDQ4622807

B. L. S. Prakasa Rao

Publication date: 18 February 2019

Published in: Stochastic Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07362994.2018.1462714

zbMATH Keywords

consistencyasymptotic normalitymaximum likelihood estimationBayes estimationBernstein-von Mises theoremmixed fractional Brownian motionmixed fractional Ornstein-Uhlenbeck processlinear stochastic differential equations

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Fractional processes, including fractional Brownian motion (60G22) Bayesian inference (62F15) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10)

Related Items (5)

Parametric inference for stochastic differential equations driven by a mixed fractional Brownian motion with random effects based on discrete observations ⋮ Maximum likelihood estimation for stochastic differential equations driven by a mixed fractional Brownian motion with random effects ⋮ Fractional processes and their statistical inference: an overview ⋮ Nonparametric estimation of trend for stochastic differential equations driven by mixed fractional Brownian motion ⋮ Nonparametric estimation for stochastic differential equations driven by mixed fractional Brownian motion with random effects

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